Seasonal Adjustment / Factors

A topic of conversation that continues to be an issue is that of seasonal adjustment. Did the U.S. economy really add 163,000 jobs last month or was it a loss of over 1.2 million? Well, technically, the answer is both are correct. On a non-seasonally adjusted basis Total Nonfarm Employment in the U.S. declined 1.2 million in July (preliminary estimate), however employment has a consistently predictable seasonal pattern to it and ignoring this pattern means one loses the forest for the trees. To gauge the health of the labor market we care about the underlying trend, not the predictable month to month movements that happen every year (last July the US lost 1.3 million NSA). To extract the signal from the noise, the Bureau of Labor Statistics applies seasonal factors to each industry’s employment data. The graph below shows both Oregon’s non-seasonally adjusted employment and its seasonally adjusted data. The seasonal patterns are clearly visible.

One line of argument is that the Great Recession affected the seasonal patterns to such a degree that the current set of seasonal factors used misrepresents the true trends in the economy. The strength and weaknesses reported in the data are due more to incorrect seasonal factors than to anything fundamental in the data. While our office does not believe that to be the case, the Oregon Employment Department has done some research on seasonality in Oregon’s labor market data. See this 2010 article on seasonal adjustments more broadly, while this more recent blog post applies pre-recession seasonal factors to post-recession employment data illustrating that while the specific month to month figures would differ – since the seasonal factors do change over time – the underlying trend and story remains intact. The remainder of this post simply illustrates some of the seasonal factor changes over time in Oregon.

Oregon’s employment is more seasonal than both the nation overall and the median state, however this seasonality has generally been declining over the past 20 years.

However this decline pales in comparison to the changes seen over the past 65 years.

One reason for this are the fundamental changes to the economy itself. Two highly seasonal industries such as Construction and Manufacturing used to make up a much larger portion of statewide employment than they do today. In fact, back in the late 1940s, Construction and Manufacturing accounted for nearly 40% of all jobs in Oregon, while today they account for only around 15% and during the housing boom they were just 18%. As seen below the seasonality of both Construction and Manufacturing have been declining over time while the seasonality of all other industries has remained, more or less, steady in comparison even though those factors continue to evolve with the economy as well.

Two points. It is unlikely that the underlying weather patterns have changed to such a degree as to warrant the massive reductions in Construction seasonal factors. It is important to keep in mind that Construction activity is largely dependent upon other businesses’ investment needs and demands. As a larger and larger portion of the economy has less and less seasonal fluctuations itself, their construction needs are likely to be less seasonal as well. That being said, Construction is still a very seasonal sector. Second, part of the reduced seasonality in Manufacturing has to do with the composition of the industry sub-sectors. Wood Products are no longer the dominant sub-sector and Computer and Electronic Product Manufacturing has very little seasonality. The following graph shows the seasonal factors used in our economic model for Food Manufacturing in blue and Computer and Electronic Products in red. The lack of seasonal movements in Computer and Electronic Product Manufacturing is striking when compared to Food. (Note the abbreviations refer to the industry’s 3 digit NAICS. 311 for Food and 334 for Computers.)

While seasonality will always exist in many different data series (we buy back to school supplies in August, we build more homes in the spring and summer, we purchase holiday gifts in November and December and some of us even in January, etc) the fundamental goal of seasonal adjustments is to be able to examine the underlying trends in the data. There are a few different techniques available to extract trends however the seasonal factors used by the Bureau of Labor Statistics do an overall good job for the employment data. Also, with the increases seen in office-type and service-oriented employment in the developed world’s economies, the reduction in overall seasonality in the economy is not unexpected, even as some industries remain significantly seasonal. While these office and service employees may bemoan the air conditioner or heater breaking, the fact remains that these occupations are significantly less reliant on good weather or the annual harvest cycle than the dominant industries of just a couple generations ago.